Multi-carrier communications with adaptive cluster configuration and switching

ABSTRACT

A method and apparatus for allocating subcarriers in an orthogonal frequency division multiple access (OFDMA) system is described. In one embodiment, the method comprises allocating at least one diversity cluster of subcarriers to a first subscriber and allocating at least one coherence cluster to a second subscriber.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a Continuation of U.S. patent application Ser. No.11/592,084 filed Nov. 2, 2006 entitled MULTI-CARRIER COMMUNICATIONS WITHADAPTIVE CLUSTER CONFIGURATION AND SWITCHING, which is a Continuation ofU.S. Pat. No. 7,146,172 issued Dec. 5, 2006 entitled MULTI-CARRIERCOMMUNICATIONS WITH ADAPTIVE CLUSTER CONFIGURATION AND SWITCHING, whichis a Continuation-in-Part of U.S. Pat. No. 6,947,748 issued Sep. 20,2005, entitled OFDMA WITH ADAPTIVE SUBCARRIER-CLUSTER CONFIGURATION ANDSELECTIVE LOADING, the disclosures of which are incorporated herein byreference.

FIELD OF THE INVENTION

The invention relates to the field of wireless communications; moreparticularly, the invention relates to multi-cell, multi-subscriberwireless systems using orthogonal frequency division multiplexing(OFDM).

BACKGROUND OF THE INVENTION

Orthogonal frequency division multiplexing (OFDM) is an efficientmodulation scheme for signal transmission over frequency-selectivechannels. In OFDM, a wide bandwidth is divided into multiple narrowbandsubcarriers, which are arranged to be orthogonal with each other. Thesignals modulated on the subcarriers are transmitted in parallel. Formore information, see Cimini, Jr., “Analysis and Simulation of a DigitalMobile Channel Using Orthogonal Frequency Division Multiplexing,” IEEETrans. Commun., vol. COM-33, no. 7, July 1985, pp. 665-75; Chuang andSollenberger, “Beyond 3G: Wideband Wireless Data Access Based on OFDMand Dynamic Packet Assignment,” IEEE Communications Magazine, Vol. 38,No. 7, pp. 78-87, July 2000.

One way to use OFDM to support multiple access for multiple subscribersis through time division multiple access (TDMA), in which eachsubscriber uses all the subcarriers within its assigned time slots.Orthogonal frequency division multiple access (OFDMA) is another methodfor multiple access, using the basic format of OFDM. In OFDMA, multiplesubscribers simultaneously use different subcarriers, in a fashionsimilar to frequency division multiple access (FDMA). For moreinformation, see Sari and Karam, “Orthogonal Frequency-Division MultipleAccess and its Application to CATV Networks,” European Transactions onTelecommunications, Vol. 9 (6), pp. 507-516, November/December 1998 andNogueroles, Bossert, Donder, and Zyablov, “Improved Performance of aRandom OFDMA Mobile Communication System,” Proceedings of IEEE VTC'98,pp. 2502-2506.

Multipath Causes Frequency-Selective Fading. The channel gains aredifferent for different subcarriers. Furthermore, the channels aretypically uncorrelated for different subscribers. The subcarriers thatare in deep fade for one subscriber may provide high channel gains foranother subscriber. Therefore, it is advantageous in an OFDMA system toadaptively allocate the subcarriers to subscribers so that eachsubscriber enjoys a high channel gain. For more information, see Wong etal., “Multiuser OFDM with Adaptive Subcarrier, Bit and PowerAllocation,” IEEE J. Select. Areas Commun., Vol. 17(10), pp. 1747-1758,October 1999.

Within one cell, the subscribers can be coordinated to have differentsubcarriers in OFDMA. The signals for different subscribers can be madeorthogonal and there is little intracell interference. However, withaggressive frequency reuse plan, e.g., the same spectrum is used formultiple neighboring cells, the problem of intercell interferencearises. It is clear that the intercell interference in an OFDMA systemis also frequency selective and it is advantageous to adaptivelyallocate the subcarriers so as to mitigate the effect of intercellinterference.

One approach to subcarrier allocation for OFDMA is a joint optimizationoperation, not only requiring the activity and channel knowledge of allthe subscribers in all the cells, but also requiring frequentrescheduling every time an existing subscriber is dropped off thenetwork or a new subscriber is added onto the network. This is oftenimpractical in real wireless system, mainly due to the bandwidth costfor updating the subscriber information and the computation cost for thejoint optimization.

SUMMARY OF THE INVENTION

A method and apparatus for allocating subcarriers in an orthogonalfrequency division multiple access (OFDMA) system is described. In oneembodiment, the method comprises allocating at least one diversitycluster of subcarriers to a first subscriber and allocating at least onecoherence cluster to a second subscriber.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention will be understood more fully from the detaileddescription given below and from the accompanying drawings of variousembodiments of the invention, which, however, should not be taken tolimit the invention to the specific embodiments, but are for explanationand understanding only.

FIG. 1A illustrates subcarriers and clusters.

FIG. IB is a flow diagram of one embodiment of a process for allocatingsubcarriers.

FIG. 2 illustrates time and frequency grid of OFDM symbols, pilots andclusters.

FIG. 3 illustrates subscriber processing.

FIG. 4 illustrates one example of FIG. 3.

FIG. 5 illustrates one embodiment of a format for arbitrary clusterfeedback.

FIG. 6 illustrates one embodiment of a partition the clusters intogroups.

FIG. 7 illustrates one embodiment of a feedback format for group-basedcluster allocation.

FIG. 8 illustrates frequency reuse and interference in a multi-cell,multi-sector network.

FIG. 9 illustrates different cluster formats for coherence clusters anddiversity clusters.

FIG. 10 illustrates diversity clusters with subcarrier hopping.

FIG. 11 illustrates intelligent switching between diversity clusters andcoherence clusters depending on subscribers mobility.

FIG. 12 illustrates one embodiment of a reconfiguration of clusterclassification.

FIG. 13 illustrates one embodiment of a base station.

DETAILED DESCRIPTION OF THE PRESENT INVENTION

A method and apparatus for allocating subcarriers in an orthogonalfrequency division multiple access (OFDMA) system is described. In oneembodiment, the method comprises allocating at least one diversitycluster of subcarriers to a first subscriber and allocating at least onecoherence cluster to a second subscriber.

The techniques disclosed herein are described using OFDMA (clusters) asan example. However, they are not limited to OFDMA-based systems. Thetechniques apply to multi-carrier systems in general, where, forexample, a carrier can be a cluster in OFDMA, a spreading code in CDMA,an antenna beam in SDMA (space-division multiple access), etc. In oneembodiment, subcarrier allocation is performed in each cell separately.Within each cell, the allocation for individual subscribers (e.g.,mobiles) is also made progressively as each new subscriber is added tothe system as opposed to joint allocation for subscribers within eachcell in which allocation decisions are made taking into account allsubscribers in a cell for each allocation.

For downlink channels, each subscriber first measures the channel andinterference information for all the subcarriers and then selectsmultiple subcarriers with good performance (e.g., a highsignal-to-interference plus noise ratio (SINR)) and feeds back theinformation on these candidate subcarriers to the base station. Thefeedback may comprise channel and interference information (e.g.,signal-to-interference-plus-noise-ratio information) on all subcarriersor just a portion of subcarriers. In case of providing information ononly a portion of the subcarriers, a subscriber may provide a list ofsubcarriers ordered starting with those subcarriers which the subscriberdesires to use, usually because their performance is good or better thanthat of other subcarriers.

Upon receiving the information from the subscriber, the base stationfurther selects the subcarriers among the candidates, utilizingadditional information available at the base station, e.g., the trafficload information on each subcarrier, amount of traffic requests queuedat the base station for each frequency band, whether frequency bands areoverused, and/or how long a subscriber has been waiting to sendinformation. In one embodiment, the subcarrier loading information ofneighboring cells can also be exchanged between base stations. The basestations can use this information in subcarrier allocation to reduceinter-cell interference.

In one embodiment, the selection by the base station of the channels toallocate, based on the feedback, results in the selection ofcoding/modulation rates. Such coding/modulation rates may be specifiedby the subscriber when specifying subcarriers that it finds favorable touse. For example, if the SINR is less than a certain threshold (e.g., 12dB), quadrature phase shift keying (QPSK) modulation is used; otherwise,16 quadrature amplitude modulation (QAM) is used. Then the base stationinforms the subscribers about the subcarrier allocation and thecoding/modulation rates to use.

In one embodiment, the feedback information for downlink subcarrierallocation is transmitted to the base station through the uplink accesschannel, which occurs in a short period every transmission time slot,e.g., 400 microseconds in every 10-millisecond time slot. In oneembodiment, the access channel occupies the entire frequency bandwidth.Then the base station can collect the uplink SINR of each subcarrierdirectly from the access channel. The SINR as well as the traffic loadinformation on the uplink subcarriers are used for uplink subcarrierallocation.

For either direction, the base station makes the final decision ofsubcarrier allocation for each subscriber.

In the following description, a procedure of selective subcarrierallocation is also disclosed, including methods of channel andinterference sensing, methods of information feedback from thesubscribers to the base station, and algorithms used by the base stationfor subcarrier selections.

In the following description, numerous details are set forth to providea thorough understanding of the present invention. It will be apparent,however, to one skilled in the art, that the present invention may bepracticed without these specific details. In other instances, well-knownstructures and devices are shown in block diagram form, rather than indetail, in order to avoid obscuring the present invention.

Some portions of the detailed descriptions which follow are presented interms of algorithms and symbolic representations of operations on databits within a computer memory. These algorithmic descriptions andrepresentations are the means used by those skilled in the dataprocessing arts to most effectively convey the substance of their workto others skilled in the art. An algorithm is here, and generally,conceived to be a self-consistent sequence of steps leading to a desiredresult. The steps are those requiring physical manipulations of physicalquantities. Usually, though not necessarily, these quantities take theform of electrical or magnetic signals capable of being stored,transferred, combined, compared, and otherwise manipulated. It hasproven convenient at times, principally for reasons of common usage, torefer to these signals as bits, values, elements, symbols, characters,terms, numbers, or the like.

It should be borne in mind, however, that all of these and similar termsare to be associated with the appropriate physical quantities and aremerely convenient labels applied to these quantities. Unlessspecifically stated otherwise as apparent from the following discussion,it is appreciated that throughout the description, discussions utilizingterms such as “processing” or “computing” or “calculating” or“determining” or “displaying” or the like, refer to the action andprocesses of a computer system, or similar electronic computing device,that manipulates and transforms data represented as physical(electronic) quantities within the computer system's registers andmemories into other data similarly represented as physical quantitieswithin the computer system memories or registers or other suchinformation storage, transmission or display devices.

The present invention also relates to apparatus for performing theoperations herein. This apparatus may be specially constructed for therequired purposes, or it may comprise a general purpose computerselectively activated or reconfigured by a computer program stored inthe computer. Such a computer program may be stored in a computerreadable storage medium, such as, but is not limited to, any type ofdisk including floppy disks, optical disks, CD-ROMs, andmagnetic-optical disks, read-only memories (ROMs), random accessmemories (RAMs), EPROMs, EEPROMs, magnetic or optical cards, or any typeof media suitable for storing electronic instructions, and each coupledto a computer system bus.

The algorithms and displays presented herein are not inherently relatedto any particular computer or other apparatus. Various general purposesystems may be used with programs in accordance with the teachingsherein, or it may prove convenient to construct more specializedapparatus to perform the required method steps. The required structurefor a variety of these systems will appear from the description below.In addition, the present invention is not described with reference toany particular programming language. It will be appreciated that avariety of programming languages may be used to implement the teachingsof the invention as described herein.

A machine-readable medium includes any mechanism for storing ortransmitting information in a form readable by a machine (e.g., acomputer). For example, a machine-readable medium includes read onlymemory (“ROM”); random access memory (“RAM”); magnetic disk storagemedia; optical storage media; flash memory devices; electrical, optical,acoustical or other form of propagated signals (e.g., carrier waves,infrared signals, digital signals, etc.); etc.

Subcarrier Clustering

The techniques described herein are directed to subcarrier allocationfor data traffic channels. In a cellular system, there are typicallyother channels, pre-allocated for the exchange of control informationand other purposes. These channels often include down link and up linkcontrol channels, uplink access channels, and time and frequencysynchronization channels.

FIG. 1A illustrates multiple subcarriers, such as subcarrier 101, andcluster 102. A cluster, such as cluster 102, is defined as a logicalunit that contains at least one physical subcarrier, as shown in FIG.1A. A cluster can contain consecutive or disjoint subcarriers. Themapping between a cluster and its subcarriers can be fixed orreconfigurable. In the latter case, the base station informs thesubscribers when the clusters are redefined. In one embodiment, thefrequency spectrum includes 512 subcarriers and each cluster includesfour consecutive subcarriers, thereby resulting in 128 clusters.

An Exemplary Subcarrier/Cluster Allocation Procedure

FIG. 1B is a flow diagram of one embodiment of a process for allocationclusters to subscribers. The process is performed by processing logicthat may comprise hardware (e.g., dedicated logic, circuitry, etc.),software (such as that which runs on, for example, a general purposecomputer system or dedicated machine), or a combination of both.

Referring to FIG. 1B, each base station periodically broadcasts pilotOFDM symbols to every subscriber within its cell (or sector) (processingblock 101). The pilot symbols, often referred to as a sounding sequenceor signal, are known to both the base station and the subscribers. Inone embodiment, each pilot symbol covers the entire OFDM frequencybandwidth. The pilot symbols may be different for different cells (orsectors). The pilot symbols can serve multiple purposes: time andfrequency synchronization, channel estimation andsignal-to-interference/noise (SINR) ratio measurement for clusterallocation.

Next, each subscriber continuously monitors the reception of the pilotsymbols and measures the SINR and/or other parameters, includinginter-cell interference and intra-cell traffic, of each cluster(processing block 102). Based on this information, each subscriberselects one or more clusters with good performance (e.g., high SINR andlow traffic loading) relative to each other and feeds back theinformation on these candidate clusters to the base station throughpredefined uplink access channels (processing block 103). For example,SINR values higher than 10 dB may indicate good performance. Likewise, acluster utilization factor less than 50% may be indicative of goodperformance. Each subscriber selects the clusters with relatively betterperformance than others. The selection results in each subscriberselecting clusters they would prefer to use based on the measuredparameters.

In one embodiment, each subscriber measures the SINR of each subcarriercluster and reports these SINR measurements to their base stationthrough an access channel. The SINR value may comprise the average ofthe SINR values of each of the subcarriers in the cluster.Alternatively, the SINR value for the cluster may be the worst SINRamong the SINR values of the subcarriers in the cluster. In stillanother embodiment, a weighted averaging of SINR values of thesubcarriers in the cluster is used to generate an SINR value for thecluster. This may be particularly useful in diversity clusters where theweighting applied to the subcarriers may be different.

The feedback of information from each subscriber to the base stationcontains a SINR value for each cluster and also indicates thecoding/modulation rate that the subscriber desires to use. No clusterindex is needed to indicate which SINR value in the feedback correspondsto which cluster as long as the order of information in the feedback isknown to the base station. In an alternative embodiment, the informationin the feedback is ordered according to which clusters have the bestperformance relative to each other for the subscriber. In such a case,an index is needed to indicate to which cluster the accompanying SINRvalue corresponds.

Upon receiving the feedback from a subscriber, the base station furtherselects one or more clusters for the subscriber among the candidates(processing block 104). The base station may utilize additionalinformation available at the base station, e.g., the traffic loadinformation on each subcarrier, amount of traffic requests queued at thebase station for each frequency band, whether frequency bands areoverused, and how long a subscriber has been waiting to sendinformation. The subcarrier loading information of neighboring cells canalso be exchanged between base stations. The base stations can use thisinformation in subcarrier allocation to reduce inter-cell interference.

After cluster selection, the base station notifies the subscriber aboutthe cluster allocation through a downlink common control channel orthrough a dedicated downlink traffic channel if the connection to thesubscriber has already been established processing block 105). In oneembodiment, the base station also informs the subscriber about theappropriate modulation/coding rates.

Once the basic communication link is established, each subscriber cancontinue to send the feedback to the base station using a dedicatedtraffic channel (e.g., one or more predefined uplink access channels).

In one embodiment, the base station allocates all the clusters to beused by a subscriber at once. In an alternative embodiment, the basestation first allocates multiple clusters, referred to herein as thebasic clusters, to establish a data link between the base station andthe subscriber. The base station then subsequently allocates moreclusters, referred to herein as the auxiliary clusters, to thesubscriber to increase the communication bandwidth. Higher prioritiescan be given to the assignment of basic clusters and lower prioritiesmay be given to that of auxiliary clusters. For example, the basestation first ensures the assignment of the basic clusters to thesubscribers and then tries to satisfy further requests on the auxiliaryclusters from the subscribers. Alternatively, the base station mayassign auxiliary clusters to one or more subscribers before allocatingbasic clusters to other subscribers. For example, a base station mayallocate basic and auxiliary clusters to one subscriber beforeallocating any clusters to other subscribers. In one embodiment, thebase station allocates basic clusters to a new subscriber and thendetermines if there are any other subscribers requesting clusters. Ifnot, then the base station allocates the auxiliary clusters to that newsubscriber.

From time to time, processing logic performs retraining by repeating theprocess described above (processing block 106). The retraining may beperformed periodically. This retraining compensates for subscribermovement and any changes in interference. In one embodiment, eachsubscriber reports to the base station its updated selection of clustersand their associated SINRs. Then the base station further performs thereselection and informs the subscriber about the new cluster allocation.Retraining can be initiated by the base station, and in which case, thebase station requests a specific subscriber to report its updatedcluster selection. Retraining can also be initiated by the subscriberwhen it observes channel deterioration.

Adaptive Modulation and Coding

In one embodiment, different modulation and coding rates are used tosupport reliable transmission over channels with different SINR. Signalspreading over multiple subcarriers may also be used to improve thereliability at very low SINR.

An example coding/modulation table is given below in Table 1.

TABLE 1 Scheme Modulation Code Rate 0 QPSK, ⅛ Spreading ½ 1 QPSK, ¼Spreading ½ 2 QPSK, ½ Spreading ½ 3 QPSK ½ 4 8PSK ⅔ 5 16QAM ¾ 6 64QAM ⅚

In the example above, ⅛ spreading indicates that one QPSK modulationsymbol is repeated over eight subcarriers. The repetition/spreading mayalso be extended to the time domain. For example, one QPSK symbol can berepeated over four subcarriers of two OFDM symbols, resulting also ⅛spreading.

The coding/modulation rate can be adaptively changed according to thechannel conditions observed at the receiver after the initial clusterallocation and rate selection.

Pilot Symbols and SINR Measurement

In one embodiment, each base station transmits pilot symbolssimultaneously, and each pilot symbol occupies the entire OFDM frequencybandwidth, as shown in FIGS. 2A-C. Referring to FIGS. 2A-C, pilotsymbols 201 are shown traversing the entire OFDM frequency bandwidth forcells A, B and C, respectively. In one embodiment, each of the pilotsymbols have a length or duration of 128 microseconds with a guard time,the combination of which is approximately 152 microseconds. After eachpilot period, there are a predetermined number of data periods followedby another set of pilot symbols. In one embodiment, there are four dataperiods used to transmit data after each pilot, and each of the dataperiods is 152 microseconds.

A subscriber estimates the SINR for each cluster from the pilot symbols.In one embodiment, the subscriber first estimates the channel response,including the amplitude and phase, as if there is no interference ornoise. Once the channel is estimated, the subscriber calculates theinterference/noise from the received signal.

The estimated SINR values may be ordered from largest to smallest SINRsand the clusters with large SINR values are selected. In one embodiment,the selected clusters have SINR values that are larger than the minimumSINR which still allows a reliable (albeit low-rate) transmissionsupported by the system. The number of clusters selected may depend onthe feedback bandwidth and the request transmission rate. In oneembodiment, the subscriber always tries to send the information about asmany clusters as possible from which the base station chooses.

The estimated SINR values are also used to choose the appropriatecoding/modulation rate for each cluster as discussed above. By using anappropriate SINR indexing scheme, an SINR index may also indicate aparticular coding and modulation rate that a subscriber desires to use.Note that even for the same subscribers, different clusters can havedifferent modulation/coding rates.

Pilot symbols serve an additional purpose in determining interferenceamong the cells. Since the pilots of multiple cells are broadcast at thesame time, they will interfere with each other (because they occupy theentire frequency band). This collision of pilot symbols may be used todetermine the amount of interference as a worst case scenario.Therefore, in one embodiment, the above SINR estimation using thismethod is conservative in that the measured interference level is theworst-case scenario, assuming that all the interference sources are on.Thus, the structure of pilot symbols is such that it occupies the entirefrequency band and causes collisions among different cells for use indetecting the worst case SINR in packet transmission systems.

During data traffic periods, the subscribers can determine the level ofinterference again. The data traffic periods are used to estimate theintra-cell traffic as well as the inter-cell interference level.Specifically, the power difference during the pilot and traffic periodsmay be used to sense the (intra-cell) traffic loading and inter-cellinterference to select the desirable clusters.

The interference level on certain clusters may be lower, because theseclusters may be unused in the neighboring cells. For example, in cell A,with respect to cluster A there is less interference because cluster Ais unused in cell B (while it is used in cell C). Similarly, in cell A,cluster B will experience lower interference from cell B because clusterB is used in cell B but not in cell C.

The modulation/coding rate based on this estimation is robust tofrequent interference changes resulted from bursty packet transmission.This is because the rate prediction is based on the worst case situationin which all interference sources are transmitting.

In one embodiment, a subscriber utilizes the information available fromboth the pilot symbol periods and the data traffic periods to analyzethe presence of both the intra-cell traffic load and inter-cellinterference. The goal of the subscriber is to provide an indication tothe base station as to those clusters that the subscriber desires touse. Ideally, the result of the selection by the subscriber is clusterswith high channel gain, low interference from other cells, and highavailability. The subscriber provides feedback information that includesthe results, listing desired clusters in order or not as describedherein.

FIG. 3 illustrates one embodiment of subscriber processing. Theprocessing is performed by processing logic that may comprise hardware(e.g., dedicated logic, circuitry, etc.), software (such as that whichruns on, for example, a general purpose computer system or dedicatedmachine), or a combination of both.

Referring to FIG. 3, channel/interference estimation processing block301 performs channel and interference estimation in pilot periods inresponse to pilot symbols. Traffic/interference analysis processingblock 302 performs traffic and interference analysis in data periods inresponse to signal information and information from channel/interferenceestimation block 301.

Cluster ordering and rate prediction processing block 303 is coupled tooutputs of channel/interference estimation processing block 301 andtraffic/interference analysis processing block 302 to perform clusterordering and selection along with rate prediction.

The output of cluster ordering processing block 303 is input to clusterrequest processing block 304, which requests clusters andmodulation/coding rates. Indications of these selections are sent to thebase station. In one embodiment, the SINR on each cluster is reported tothe base station through an access channel. The information is used forcluster selection to avoid clusters with heavy intra-cell trafficloading and/or strong interference from other cells. That is, a newsubscriber may not be allocated use of a particular cluster if heavyintra-cell traffic loading already exists with respect to that cluster.Also, clusters may not be allocated if the interference is so strongthat the SINR only allows for low-rate transmission or no reliabletransmission at all.

The channel/interference estimation by processing block 301 iswell-known in the art by monitoring the interference that is generateddue to full-bandwidth pilot symbols being simultaneously broadcast inmultiple cells. The interface information is forwarded to processingblock 302 which uses the information to solve the following equation:H _(i) S _(i) +I _(i) +n _(i) =y _(i)where S_(i) represents the signal for subcarrier (freq. band) i, I_(i)is the interference for subcarrier i, n_(i) is the noise associated withsubcarrier i, and y_(i) is the observation for subcarrier i. In the caseof 512 subcarriers, i may range from 0 to 511. The I_(i) and n_(i) arenot separated and may be considered one quantity. The interference/noiseand channel gain H_(i) are not known. During pilot periods, the signalS_(i) representing the pilot symbols, and the observation y_(i) areknowns, thereby allowing determination of the channel gain H_(i) for thecase where there is no interference or noise. Once this is known, it maybe plugged back into the equation to determine the interference/noiseduring data periods since H_(i), S_(i) and y_(i) are all known.

The interference information from processing blocks 301 and 302 are usedby the subscriber to select desirable clusters. In one embodiment usingprocessing block 303, the subscriber orders clusters and also predictsthe data rate that would be available using such clusters. The predicteddata rate information may be obtained from a look up table withprecalculated data rate values. Such a look up table may store the pairsof each SINR and its associated desirable transmission rate. Based onthis information, the subscriber selects clusters that it desires to usebased on predetermined performance criteria. Using the ordered list ofclusters, the subscriber requests the desired clusters along with codingand modulation rates known to the subscriber to achieve desired datarates.

FIG. 4 is one embodiment of an apparatus for the selection of clustersbased on power difference. The approach uses information availableduring both pilot symbol periods and data traffic periods to performenergy detection. The processing of FIG. 4 may be implemented inhardware, (e.g., dedicated logic, circuitry, etc.), software (such as isrun on, for example, a general purpose computer system or dedicatedmachine), or a combination of both.

Referring to FIG. 4, a subscriber includes SINR estimation processingblock 401 to perform SINR estimation for each cluster in pilot periods,power calculation processing block 402 to perform power calculations foreach cluster in pilot periods, and power calculation processing block403 to perform power calculations in data periods for each cluster.Subtractor 404 subtracts the power calculations for data periods fromprocessing block 403 from those in pilot periods from processing block402. The output of subtractor 404 is input to power difference ordering(and group selection) processing block 405 that performs clusterordering and selection based on SINR and the power difference betweenpilot periods and data periods. Once the clusters have been selected,the subscriber requests the selected clusters and the coding/modulationrates with processing block 406.

More specifically, in one embodiment, the signal power of each clusterduring the pilot periods is compared with that during the trafficperiods, according to the following:

$\begin{matrix}{P_{P} = {P_{S} + P_{1} + P_{N^{\prime}}}} \\{P_{D} = \left\{ \begin{matrix}{P_{N},{{with}\mspace{14mu}{no}\mspace{14mu}{signal}\mspace{14mu}{and}\mspace{14mu}{interference}}} \\{{P_{S} + P_{N}},{{with}\mspace{14mu}{signal}\mspace{14mu}{only}}} \\{{P_{I} + P_{N}},{{with}\mspace{14mu}{interference}\mspace{14mu}{only}}} \\{{P_{S} + P_{I} + P_{N}},\;{{with}\mspace{14mu}{both}\mspace{14mu}{signal}\mspace{14mu}{and}\mspace{14mu}{interference}}}\end{matrix} \right.} \\{{P_{p} - P_{D}} = \left\{ \begin{matrix}{{P_{S} + P_{I}},{{with}\mspace{14mu}{no}\mspace{14mu}{signal}\mspace{14mu}{and}\mspace{14mu}{interference}}} \\{P_{I},{{with}\mspace{14mu}{signal}\mspace{14mu}{only}}} \\{P_{S},{{with}\mspace{14mu}{interference}\mspace{14mu}{only}}} \\{O,{{with}\mspace{14mu}{both}\mspace{14mu}{signal}\mspace{14mu}{and}\mspace{14mu}{interference}}}\end{matrix} \right.}\end{matrix}$where P_(P) is the measured power corresponding to each cluster duringpilot periods, P_(D) is the measured power during the traffic periods,P_(S) is the signal power, P_(I) is the interference power, and P_(N) isthe noise power.

In one embodiment, the subscriber selects clusters with relatively largeP_(P)/(P_(P)−P_(D)) (e.g., larger than a threshold such as 10 dB) andavoids clusters with low P_(P)/(P_(P)−P_(D)) (e.g., lower than athreshold such as 10 dB) when possible.

Alternatively, the difference may be based on the energy differencebetween observed samples during the pilot period and during the datatraffic period for each of the subcarriers in a cluster such as thefollowing:Δ_(i) =|y _(i) ^(P) |−|y _(i) ^(D)|Thus, the subscriber sums the differences for all subcarriers.

Depending on the actual implementation, a subscriber may use thefollowing metric, a combined function of both SINR and P_(P)−P_(D), toselect the clusters:β=ƒ(SINR, P _(P)/(P _(P) −P _(D))where ƒ is a function of the two inputs. One example of ƒ is weightedaveraging (e.g., equal weights). Alternatively, a subscriber selects acluster based on its SINR and only uses the power difference P_(P)−P_(D)to distinguish clusters with similar SINR. The difference may be smallerthan a threshold (e.g., 1 dB).

Both the measurement of SINR and P_(P)−P_(D) can be averaged over timeto reduce variance and improve accuracy. In one embodiment, amoving-average time window is used that is long enough to average outthe statistical abnormity yet short enough to capture the time-varyingnature of channel and interference, e.g., 1 millisecond.

Feedback Format for Downlink Cluster Allocation

In one embodiment, for the downlink, the feedback contains both theindices of selected clusters and their SINR. An exemplary format forarbitrary cluster feedback is shown in FIG. 5. Referring to FIG. 5, thesubscriber provides a cluster index (ID) to indicate the cluster and itsassociated SINR value. For example, in the feedback, the subscriberprovides cluster ID1 (501) and the SINR for the cluster, SINR1 (502),cluster ID2 (503) and the SINR for the cluster, SINR2 (504), and clusterID3 (505), and the SINR for the cluster, SINR3 (506), etc. The SINR forthe cluster may be created using an average of the SINRs of thesubcarriers. Thus, multiple arbitrary clusters can be selected as thecandidates. As discussed above, the selected clusters can also beordered in the feedback to indicate priority. In one embodiment, thesubscriber may form a priority list of clusters and sends back the SINKinformation in a descending order of priority.

Typically, an index to the SINR level, instead of the SINR itself issufficient to indicate the appropriate coding/modulation for thecluster. For example, a 3-bit field can be used for SINR indexing toindicate 8 different rates of adaptive coding/modulation.

An Exemplary Base Station

The base station assigns desirable clusters to the subscriber making therequest. In one embodiment the availability of the cluster forallocation to a subscriber depends on the total traffic load on thecluster. Therefore, the base station selects the clusters not only withhigh SINR, but also with low traffic load.

FIG. 13 is a block diagram of one embodiment of a base station.Referring to FIG. 13, cluster allocation and load scheduling controller1301 (cluster allocator) collects all the necessary information,including the downlink/uplink SINR of clusters specified for eachsubscriber (e.g., via SINR/rate indices signals 1313 received from OFDMtransceiver 1305) and user data, queue fullness/traffic load (e.g., viauser data buffer information 1311 from multi-user data buffer 1302).Using this information, controller 1301 makes the decision on clusterallocation and load scheduling for each user, and stores the decisioninformation in a memory (not shown). Controller 1301 informs thesubscribers about the decisions through control signal channels (e.g.,control signal/cluster allocation 1312 via OFDM transceiver 1305).Controller 1301 updates the decisions during retraining.

In one embodiment, controller 1301 also performs admission control touser access since it knows the traffic load of the system. This may beperformed by controlling user data buffers 1302 using admission controlsignals 1310.

The packet data of User 1˜N are stored in the user data buffers 1302.For downlink, with the control of controller 1301, multiplexer 1303loads the user data to cluster data buffers (for Cluster 1˜M) waiting tobe transmitted. For the uplink, multiplexer 1303 sends the data in thecluster buffers to the corresponding user buffers. Cluster buffer 1304stores the signal to be transmitted through OFDM transceiver 1305 (fordownlink) and the signal received from transceiver 1305. In oneembodiment, each user might occupy multiple clusters and each clustermight be shared by multiple users (in a time-division-multiplexingfashion).

Group-Based Cluster Allocation

In another embodiment, for the downlink, the clusters are partitionedinto groups. Each group can include multiple clusters. FIG. 6illustrates an exemplary partitioning. Referring to FIG. 6, groups 1-4are shown with arrows pointing to clusters that are in each group as aresult of the partitioning. In one embodiment, the clusters within eachgroup are spaced far apart over the entire bandwidth. In one embodiment,the clusters within each group are spaced apart farther than the channelcoherence bandwidth, i.e. the bandwidth within which the channelresponse remains roughly the same. A typical value of coherencebandwidth is 100 kHz for many cellular systems. This improves frequencydiversity within each group and increases the probability that at leastsome of the clusters within a group can provide high SINR. The clustersmay be allocated in groups.

Goals of group-based cluster allocation include reducing the data bitsfor cluster indexing, thereby reducing the bandwidth requirements of thefeedback channel (information) and control channel (information) forcluster allocation. Group-based cluster allocation may also be used toreduce inter-cell interference.

After receiving the pilot signal from the base station, a subscribersends back the channel information on one or more cluster groups,simultaneously or sequentially. In one embodiment, only the informationon some of the groups is sent back to the base station. Many criteriacan be used to choose and order the groups, based on the channelinformation, the inter-cell interference levels, and the intra-celltraffic load on each cluster.

In one embodiment, a subscriber first selects the group with the bestoverall performance and then feedbacks the SINR information for theclusters in that group. The subscriber may order the groups based ontheir number of clusters for which the SINR is higher than a predefinedthreshold. By transmitting the SINR of all the clusters in the groupsequentially, only the group index, instead of all the cluster indices,needs to be transmitted. Thus, the feedback for each group generallycontains two types of information: the group index and the SINR value ofeach cluster within the group. FIG. 7 illustrates an exemplary formatfor indicating a group-based cluster allocation. Referring to FIG. 7, agroup ID, ID1, is followed by the SINR values for each of the clustersin the group. This can significantly reduce the feedback overhead.

Upon receiving the feedback information from the subscriber, the clusterallocator at the base station selects multiple clusters from one or moregroups, if available, and then assigns the clusters to the subscriber.This selection may be performed by an allocation in a media accesscontrol portion of the base station.

Furthermore, in a multi-cell environment, groups can have differentpriorities associated with different cells. In one embodiment, thesubscriber's selection of a group is biased by the group priority, whichmeans that certain subscribers have higher priorities on the usage ofsome groups than the other subscribers.

In one embodiment, there is no fixed association between one subscriberand one cluster group; however, in an alternative embodiment there maybe such a fixed association. In an implementation having a fixedassociation between a subscriber and one or more cluster groups, thegroup index in the feedback information can be omitted, because thisinformation is known to both subscriber and base station by default.

In another embodiment, the pilot signal sent from the base station tothe subscriber also indicates the availability of each cluster, e.g.,the pilot signal shows which clusters have already been allocated forother subscribers and which clusters are available for new allocations.For example, the base station can transmit a pilot sequence 1111 1111 onthe subcarriers of a cluster to indicate that the cluster is available,and 1111-1-1-1-1 to indicate the cluster is not available. At thereceiver, the subscriber first distinguishes the two sequences using thesignal processing methods which are well known in the art, e.g., thecorrelation methods, and then estimates the channel and interferencelevel.

With the combination of this information and the channel characteristicsobtained by the subscriber, the subscriber can prioritize the groups toachieve both high SINR and good load balancing.

In one embodiment, the subscriber protects the feedback information byusing error correcting codes. In one embodiment, the SINR information inthe feedback is first compressed using source coding techniques, e.g.,differential encoding, and then encoded by the channel codes.

FIG. 8 shows one embodiment of a frequency reuse pattern for anexemplary cellular set up. Each cell has hexagonal structure with sixsectors using directional antennas at the base stations. Between thecells, the frequency reuse factor is one. Within each cell, thefrequency reuse factor is 2 where the sectors use two frequenciesalternatively. As shown in FIG. 8, each shaded sector uses half of theavailable OFDMA clusters and each unshaded sector uses the other half ofthe clusters. Without loss of generality, the clusters used by theshaded sectors are referred to herein as odd clusters and those used bythe unshaded sectors are referred to herein as even clusters.

Consider the downlink signaling with omni-directional antennas at thesubscribers. From FIG. 8, it is clear that for the downlink in theshaded sectors, Cell A interferes with Cell B, which in turn interfereswith Cell C, which in turn interferes with Cell A, namely, A->B->C->A.For the unshaded sectors, Cell A interferes with Cell C, which in turninterferes with Cell B, which in turn interferes with Cell A, namely,A->C->B->A.

Sector A1 receives interference from Sector C1, but its transmissioninterferes with Sector B1. Namely, its interference source and thevictims with which it interferes are not the same. This might cause astability problem in a distributed cluster-allocation system usinginterference avoidance: if a frequency cluster is assigned in Sector B1but not in Sector C1, the cluster may be assigned in A1 because it maybe seen as clean in A1. However, the assignment of this cluster A1 cancause interference problem to the existing assignment in B1.

In one embodiment, different cluster groups are assigned differentpriorities for use in different cells to alleviate the aforementionedproblem when the traffic load is progressively added to a sector. Thepriority orders are jointly designed such that a cluster can beselectively assigned to avoid interference from its interference source,while reducing, and potentially minimizing, the probability of causinginterference problem to existing assignments in other cells.

Using the aforementioned example, the odd clusters (used by the shadedsectors) are partitioned into 3 groups: Group 1, 2, 3. The priorityorders are listed in Table 2.

TABLE 2 Priority ordering for the downlink of the shaded sectors.Priority Ordering Cell A Cell B Cell C 1 Group 1 Group 3 Group 2 2 Group2 Group 1 Group 3 3 Group 3 Group 2 Group 1

Consider Sector A1. First, the clusters in Group 1 are selectivelyassigned. If there are still more subscribers demanding clusters, theclusters in Group 2 are selectively assigned to subscribers, dependingon the measured SINR (avoiding the clusters receiving stronginterference from Sector C1). Note that the newly assigned clusters fromGroup 2 to Sector A1 shall not cause interference problem in Sector B1,unless the load in Sector B1 is so heavy that the clusters in both Group3 and 1 are used up and the clusters in Group 2 are also used. Table 3shows the cluster usage when less than ⅔ of all the available clustersare used in Sector A1, B1, and C1.

TABLE 3 Cluster usage for the downlink of the shaded sectors with lessthan ⅔ of the full load. Cluster Usage Cell A Cell B Cell C 1 Group 1Group 3 Group 2 2 Group 2 Group 1 Group 3 3

Table 4 shows the priority orders for the unshaded sectors, which aredifferent from those for the shaded sectors, since the interferingrelationship is reversed.

TABLE 4 Priority ordering for the downlink of the unshaded sectors.Priority Ordering Cell A Cell B Cell C 1 Group 1 Group 2 Group 3 2 Group2 Group 3 Group 1 3 Group 3 Group 1 Group 2Intelligent Switching between Coherence and Diversity Clusters

In one embodiment, there are two categories of clusters: coherenceclusters, containing multiple subcarriers close to each other anddiversity clusters, containing multiple subcarriers with at least someof the subcarriers spread far apart over the spectrum. The closeness ofthe multiple subcarriers in coherence clusters is preferably within thechannel coherence bandwidth, i.e. the bandwidth within which the channelresponse remains roughly the same, which is typically within 100 kHz formany cellular systems. On the other hand, the spread of subcarriers indiversity clusters is preferably larger than the channel coherencebandwidth, typically within 100 kHz for many cellular systems. Ofcourse, the larger the spread, the better the diversity. Therefore, ageneral goal in such cases is to maximize the spread.

FIG. 9 illustrates exemplary cluster formats for coherence clusters anddiversity clusters for Cells A-C. Referring to FIG. 9, for cells A-C,the labeling of frequencies (subcarriers) indicates whether thefrequencies are part of coherence or diversity clusters. For example,those frequencies labeled 1-8 are diversity clusters and those labeled9-16 are coherence clusters. For example, all frequencies labeled 1 in acell are part of one diversity cluster, all frequencies labeled 2 in acell are part of another diversity cluster, etc., while the group offrequencies labeled 9 are one coherence cluster, the group offrequencies labeled 10 are another coherence cluster, etc. The diversityclusters can be configured differently for different cells to reduce theeffect of inter-cell interference through interference averaging.

FIG. 9 shows example cluster configurations for three neighboring cells.The interference from a particular cluster in one cell are distributedto many clusters in other cells, e.g., the interference from Cluster 1in Cell A are distributed to Cluster 1, 8, 7, 6 in Cell B. Thissignificantly reduces the interference power to any particular clusterin Cell B. Likewise, the interference to any particular cluster in onecell comes from many different clusters in other cells. Since not allclusters are strong interferers, diversity clusters, with channel codingacross its subcarriers, provide interference diversity gain. Therefore,it is advantageous to assign diversity clusters to subscribers that areclose (e.g., within the coherent bandwidth) to the cell boundaries andare more subject to inter-cell interference.

Since the subcarriers in a coherence cluster are consecutive or close(e.g., within the coherent bandwidth) to each other, they are likelywithin the coherent bandwidth of the channel fading. Therefore, thechannel gain of a coherence cluster can vary significantly and clusterselection can greatly improve the performance. On the other hand, theaverage channel gain of a diversity cluster has less of a degree ofvariation due to the inherent frequency diversity among the multiplesubcarriers spread over the spectrum. With channel coding across thesubcarriers within the cluster, diversity clusters are more robust tocluster mis-selection (by the nature of diversification itself), whileyielding possibly less gain from cluster selection. Channel codingacross the subcarriers means that each codeword contains bitstransmitted from multiple subcarriers, and more specifically, thedifference bits between codewords (error vector) are distributed amongmultiple subcarriers.

More frequency diversity can be obtained through subcarrier hopping overtime in which a subscriber occupies a set of subcarriers at one timeslot and another different set of subcarriers at a different time slot.One coding unit (frame) contains multiple such time slots and thetransmitted bits are encoded across the entire frame.

FIG. 10 illustrates diversity cluster with subcarrier hopping. Referringto FIG. 10, there are four diversity clusters in each of cells A and Bshown, with each subcarrier in individual diversity clusters having thesame label (1, 2, 3, or 4). There are four separate time slots shown andduring each of the time slots, the subcarriers for each of the diversityclusters change. For example, in cell A, subcarrier 1 is part ofdiversity cluster 1 during time slot 1, is part of diversity cluster 2during time slot 2, is part of diversity cluster 3 during time slot 3,and is part of diversity cluster 4 during time slot 4. Thus, moreinterference diversity can be obtained through subcarrier hopping overtime, with farther interference diversity achieved by using differenthopping patterns for different cells, as shown in FIG. 10.

The manner in which the subscriber changes the subcarriers (hoppingsequences) can be different for different cells in order to achievebetter interference averaging through coding.

For static subscribers, such as in fixed wireless access, the channelschange very little over time. Selective cluster allocation using thecoherence clusters achieves good performance. On the other hand, formobile subscribers, the channel time variance (the variance due tochanges in the channel over time) can be very large. A high-gain clusterat one time can be in deep fade at another. Therefore, clusterallocation needs to be updated at a rapid rate, causing significantcontrol overhead. In this case, diversity clusters can be used toprovide extra robustness and to alleviate the overhead of frequentcluster reallocation. In one embodiment, cluster allocation is performedfaster than the channel changing rate, which is often measured by thechannel Doppler rate (in Hz), i.e. how many cycles the channel changesper second where the channel is completely different after one cycle.Note that selective cluster allocation can be performed on bothcoherence and diversity clusters.

In one embodiment, for cells containing mixed mobile and fixedsubscribers, a channel/interference variation detector can beimplemented at either the subscriber or the base station, or both. Usingthe detection results, the subscriber and the base station intelligentlyselects diversity clusters to mobile subscribers or fixed subscribers atcell boundaries, and coherence clusters to fixed subscribers close tothe base station. The channel/interference variation detector measuresthe channel (SINR) variation from time to time for each cluster. Forexample, in one embodiment, the channel/interference detector measuresthe power difference between pilot symbols for each cluster and averagesthe difference over a moving window (e.g., 4 time slots). A largedifference indicates that channel/interference changes frequently andsubcarrier allocation may be not reliable. In such a case, diversityclusters are more desirable for the subscriber.

FIG. 11 is a flow diagram of one embodiment of a process for intelligentselection between diversity clusters and coherence clusters depending onsubscribers mobility. The process is performed by processing logic thatmay comprise hardware (e.g., circuitry, dedicated logic, etc.), software(such as that which runs on, for example, a general purpose computersystem or dedicated machine), or a combination of both.

Referring to FIG. 11, processing logic in the base station performschannel/interference variation detection (processing block 1101).Processing logic then tests whether the results of thechannel/interference variation detection indicate that the user ismobile or in a fixed position close to the edge of the cell (processingblock 1102). If the user is not mobile or is not in a fixed positionclose to the edge of the cell, processing transitions to processingblock 1103 where processing logic in the base station selects coherenceclusters; otherwise, processing transitions to processing block 1104 inwhich processing logic in the base station selects diversity clusters.

In one embodiment, the base station determines whether a subscriber ismobile or fixed by detecting a rate of change of pilot signals, or thenormalized channel variation, and determining that the rate of change isgreater than a predetermined threshold. The normalized instantaneousdifference between channels may be represented as

$\frac{{{H_{i} - H_{i + 2}}}^{2}}{{H_{i}}^{2}},$where H_(i) represents the channel and i is the index to represent theindividual channels.

The threshold is system dependent. For example, the rate of change isgreater than 10% (although any precentage (e.g., 20%) could be used),then the base station concludes that the subscriber is mobile. In oneembodiment, if the constant period in signaling is not greater than amultiple of the round trip delay (e.g., 5 times the round trip delay),then the base station determines that the subscriber is mobile andallocates diversity clusters; otherwise, the base station allocatescoherence clusters.

The selection can be updated and intelligently switched duringretraining.

The ratio/allocation of the numbers of coherence and diversity clustersin a cell depends on the ratio of the population of mobile and fixedsubscribers. When the population changes as the system evolves, theallocation of coherence and diversity clusters can be reconfigured toaccommodate the new system needs. FIG. 12 illustrates a reconfigurationof cluster classification which can support more mobile subscribers thanthat in FIG. 9.

Whereas many alterations and modifications of the present invention willno doubt become apparent to a person of ordinary skill in the art afterhaving read the foregoing description, it is to be understood that anyparticular embodiment shown and described by way of illustration is inno way intended to be considered limiting. Therefore, references todetails of various embodiments are not intended to limit the scope ofthe claims which in themselves recite only those features regarded asessential to the invention.

1. A method performed by a Base Station for allocating subcarriers in anOFDMA system, the method comprising: determining a subscriber locationwithin a cell; and selecting either a coherence cluster or a diversitycluster for the subscriber based on the subscriber's location within thecell.
 2. The method of claim 1, wherein the determining comprisesdetermining whether the subscriber is located closer to a base stationor closer to boundaries of the cell.
 3. The method of claim 2, whereinthe selecting comprises selecting the coherence cluster if thesubscriber is located closer to the base station.
 4. The method of claim2, wherein the selecting comprises selecting the diversity cluster ifthe subscriber is located closer to the boundaries of the cell.
 5. Themethod of claim 1, comprising: periodically redetermining thesubscriber's location with the cell; and in response to theredetermining, periodically reselecting either a coherence cluster or adiversity cluster for the subscriber based on the subscriber's locationwithin the cell.
 6. The method of claim 1, wherein the determiningcomprises determining the subscriber's location based on processing oneor more location indicative signals.
 7. The method of claim 6, whereinthe determining comprises determining the subscriber's location based onprocessing interference variation.
 8. The method of claim 6, wherein thedetermining comprises determining the subscriber's location based on asignal strength of the one or more location indicative signals.
 9. Abase station configured for OFDMA communication, the base stationcomprising: processing logic configured; to determine a location of asubscriber located within the base station's cell; and to select eithera coherence cluster or a diversity cluster for the subscriber based onthe subscriber's location within the cell.
 10. The base station of claim9, wherein the processing logic is configured to select the coherencecluster if the subscriber is located closer to the base station than theboundaries of the cell.
 11. The base station of claim 9, wherein theprocessing logic is configured to select the diversity cluster if thesubscriber is located closer to the boundaries of the cell than the basestation.
 12. The base station of claim 9, wherein the first processinglogic comprises hardware logic.
 13. The base station of claim 9, whereinthe processing logic is configured to determine the location based on alocation-indicative signal.
 14. The base station of claim 13, whereinthe location-indicative signal is not generated by the base station. 15.The base station of claim 13, wherein the location-indicative signal isbased on interference variation within the cell.
 16. A method performedby a mobile device for determining an SINR value for a cluster ofsubcarriers in an OFDMA system, the method comprising: measuring an SINRvalue for each subcarrier in the cluster; determining the SINR value forthe cluster based on one or more of the SINR values for the subcarrier;and reporting the SINR value for the cluster to a base station.
 17. Themethod of claim 16, wherein the determining the SINR value for thecluster comprises selecting the worst SINR value amongst the STNR valuesfor the subcarriers as the SINR value for the cluster.
 18. The method ofclaim 16, wherein the determining the SINR value for the clustercomprises performing a weighted average of the SINR values for thesubcarriers in the cluster.
 19. The method of claim 16, wherein thecluster comprises a diversity cluster and wherein the performing theweighted average comprises assigning unique weighting values to each ofthe subcarriers in the diversity cluster.